Correlation Between Swiss Leader and Xlife Sciences

Can any of the company-specific risk be diversified away by investing in both Swiss Leader and Xlife Sciences at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Swiss Leader and Xlife Sciences into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Swiss Leader Price and Xlife Sciences AG, you can compare the effects of market volatilities on Swiss Leader and Xlife Sciences and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Swiss Leader with a short position of Xlife Sciences. Check out your portfolio center. Please also check ongoing floating volatility patterns of Swiss Leader and Xlife Sciences.

Diversification Opportunities for Swiss Leader and Xlife Sciences

-0.9

Correlation Coefficient

Swiss Leader  Xlife Sciences

Pay attention - limited upside

The 3 months correlation between Swiss and Xlife is -0.9. Overlapping area represents the amount of risk that can be diversified away by holding Swiss Leader Price and Xlife Sciences AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Xlife Sciences AG and Swiss Leader is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Swiss Leader Price are associated (or correlated) with Xlife Sciences. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Xlife Sciences AG has no effect on the direction of Swiss Leader i.e., Swiss Leader and Xlife Sciences go up and down completely randomly.

Pair Corralation between Swiss Leader and Xlife Sciences

Assuming the 90 days trading horizon Swiss Leader Price is expected to generate 0.17 times more return on investment than Xlife Sciences. However, Swiss Leader Price is 5.86 times less risky than Xlife Sciences. It trades about 0.2 of its potential returns per unit of risk. Xlife Sciences AG is currently generating about -0.01 per unit of risk. If you would invest  191,700  in Swiss Leader Price on December 27, 2024 and sell it today you would earn a total of  17,945  from holding Swiss Leader Price or generate 9.36% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Significant
Accuracy	98.39%
Values	Daily Returns

Swiss Leader Price  vs.  Xlife Sciences AG

Pair Trading with Swiss Leader and Xlife Sciences

The main advantage of trading using opposite Swiss Leader and Xlife Sciences positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Swiss Leader position performs unexpectedly, Xlife Sciences can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Xlife Sciences will offset losses from the drop in Xlife Sciences' long position.

The idea behind Swiss Leader Price and Xlife Sciences AG pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Insider Screener module to find insiders across different sectors to evaluate their impact on performance.